Radiomics: the process and the challenges
…, A Dekker, D Fenstermacher, DB Goldgof… - Magnetic resonance …, 2012 - Elsevier
“Radiomics” refers to the extraction and analysis of large amounts of advanced quantitative
imaging features with high throughput from medical images obtained with computed …
imaging features with high throughput from medical images obtained with computed …
Radiomics in brain tumor: image assessment, quantitative feature descriptors, and machine-learning approaches
Radiomics describes a broad set of computational methods that extract quantitative features
from radiographic images. The resulting features can be used to inform imaging diagnosis, …
from radiographic images. The resulting features can be used to inform imaging diagnosis, …
Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons
… d 0 and d 0 while the bias claim requires only the average of the individual differences to be
between −d 0 and d … It is possible that 95% of differences are between −d 0 and d 0 , but one …
between −d 0 and d … It is possible that 95% of differences are between −d 0 and d 0 , but one …
An experimental comparison of range image segmentation algorithms
… Secon'd, documenting the state of the art for planar segmentation seems intrinsically worthwhile.
Third, the various algorithLms for sl-gmenting curved surface patches often do not allow …
Third, the various algorithLms for sl-gmenting curved surface patches often do not allow …
Automatic tumor segmentation using knowledge-based techniques
MC Clark, LO Hall, DB Goldgof… - IEEE transactions on …, 1998 - ieeexplore.ieee.org
… The thresholds used were determined from training slices by creating a 3-D histogram,
including 2-D projections, using only pixels contained in the initial tumor segmentation. Then the …
including 2-D projections, using only pixels contained in the initial tumor segmentation. Then the …
Framework for performance evaluation of face, text, and vehicle detection and tracking in video: Data, metrics, and protocol
… Dmitry Goldgof received the MS degree in computer engineering from Rensselaer Polytechnic
Institute in 1985 and the PhD degree in electrical engineering from the University of …
Institute in 1985 and the PhD degree in electrical engineering from the University of …
Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels
Purpose Many radiomics features were originally developed for non‐medical imaging
applications and therefore original assumptions may need to be reexamined. In this study, we …
applications and therefore original assumptions may need to be reexamined. In this study, we …
Understanding transit scenes: A survey on human behavior-recognition algorithms
J Candamo, M Shreve, DB Goldgof… - IEEE transactions on …, 2009 - ieeexplore.ieee.org
… Recent developments include 3-D environmental modeling reconstructed using the
shape-from-motion technique [36] and 3-D imagery from a moving monocular camera [37]. Most 3-D …
shape-from-motion technique [36] and 3-D imagery from a moving monocular camera [37]. Most 3-D …
Finding covid-19 from chest x-rays using deep learning on a small dataset
Testing for COVID-19 has been unable to keep up with the demand. Further, the false negative
rate is projected to be as high as 30% and test results can take some time to obtain. X-ray …
rate is projected to be as high as 30% and test results can take some time to obtain. X-ray …
Automatic segmentation of non-enhancing brain tumors in magnetic resonance images
LM Fletcher-Heath, LO Hall, DB Goldgof… - Artificial intelligence in …, 2001 - Elsevier
Tumor segmentation from magnetic resonance (MR) images may aid in tumor treatment by
tracking the progress of tumor growth and/or shrinkage. In this paper we present the first …
tracking the progress of tumor growth and/or shrinkage. In this paper we present the first …